8 research outputs found
Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes
Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research
Adolescent cannabis use, depression and anxiety disorders in the Northern Finland Birth Cohort 1986
Abstract
Background: Cannabis use has been associated with increased risk of psychiatric disorders. However, associations between adolescent cannabis use, depression and anxiety disorders are inconsistently reported in longitudinal samples.
Aims: To study associations of adolescent cannabis use with depression and anxiety disorders.
Method: We used data from the Northern Finland Birth Cohort 1986, linked to nationwide registers, to study the association between adolescent cannabis use and depression and anxiety disorders until 33 years of age (until 2018).
Results: We included 6325 participants (48.8% male) in the analyses; 352 (5.6%) participants reported cannabis use until 15–16 years of age. By the end of the follow-up, 583 (9.2%) participants were diagnosed with unipolar depression and 688 (10.9%) were diagnosed with anxiety disorder. Cannabis use in adolescence was associated with an increased risk of depression and anxiety disorders in crude models. After adjusting for parental psychiatric disorder, baseline emotional and behavioural problems, demographic factors and other substance use, using cannabis five or more times was associated with increased risk of anxiety disorders (hazard ratio 2.01, 95% CI 1.15–3.82), and using cannabis once (hazard ratio 1.93, 95% CI 1.30–2.87) or two to four times (hazard ratio 2.02, 95% CI 1.24–3.31) was associated with increased risk of depression.
Conclusions: Cannabis use in adolescence was associated with an increased risk of future depression and anxiety disorders. Further research is needed to clarify if this is a causal association, which could then inform public health messages about the use of cannabis in adolescence
Is early exposure to cannabis associated with bipolar disorder?:results from a Finnish birth cohort study
Abstract
Background and aims: There are few longitudinal studies assessing the association of cannabis use and subsequent onset of bipolar disorder. We aimed to measure the association between early cannabis exposure and subsequent bipolar disorder.
Design, Setting and Participants: Observational study linking a sample from the northern Finland birth cohort 1986 (n = 6325) to nation-wide register data to examine the association of life-time cannabis exposure at age 15/16 years and subsequent bipolar disorder until age 33 (until the end of 2018); 6325 individuals (48.8% males) were included in the analysis.
Measurements: Cannabis exposure was measured via self-report. Bipolar disorder was measured via bipolar disorder-related diagnostic codes (ICD-10: F30.xx, F31.xx) collected from the Care Register for Health Care 2001–18, the Register of Primary Health Care Visits 2011–18, the medication reimbursement register of the Social Insurance Institution of Finland 2001–05 and the disability pensions of the Finnish Center for Pensions 2001–16. Potential confounders included demographic characteristics, parental psychiatric disorders, emotional and behavioral problems and other substance use.
Findings: Three hundred and fifty-two adolescents (5.6%) reported any cannabis use until the age of 15–16 years. Of the whole sample, 66 (1.0%) were diagnosed with bipolar disorder. Adolescent cannabis use was associated with bipolar disorder [hazard ratio (HR) = 3.46; 95% confidence interval (CI) = 1.81–6.61]. This association remained statistically significant after adjusting for sex, family structure and parental psychiatric disorders (HR = 3.00; 95% CI = 1.47–6.13) and after further adjusting for adolescent emotional and behavioral problems (HR = 2.34; 95% CI = 1.11–4.94). Further adjustments for frequent alcohol intoxications, daily smoking and lifetime illicit drug use attenuated the associations to statistically non-significant.
Conclusions: In Finland, the positive association between early cannabis exposure and subsequent development of bipolar disorder appears to be confounded by other substance use
Does cannabis use in adolescence predict self-harm or suicide?:results from a Finnish Birth Cohort Study
Abstract
Objective: Longitudinal studies examining the association between adolescent cannabis use and self-harm are rare, heterogeneous and mixed in their conclusions. We study this association utilizing a large general population-based sample with prospective data.
Methods: The Northern Finland Birth Cohort 1986 (n = 6582) with linkage to nationwide register data was used to study the association of self-reported cannabis use at age 15–16 years and self-harm and suicide death until age 33 (until year 2018), based on register information. Cox regression analysis with Hazard Ratios (HR) and 95% confidence intervals (CI) was used. Psychiatric disorders, parental psychiatric disorders and other substance use were considered as confounders.
Results: In all, 6582 (49.2% male) were included in the analysis, and 377 adolescents (5.7%) reported any cannabis use until the age of 15–16 years. Based on register information, 79 (55.7% male) had visited in health care services due to self-harm, and 22 (90.1% male) had died by suicide. In crude analyses, adolescent cannabis use was associated with self-harm (HR = 3.93; 95% CI 2.24–6.90). The association between cannabis use and self-harm remained statistically significant after adjusting for sex, psychiatric disorders at baseline, frequent alcohol intoxications, other illicit drug use, and parental psychiatric disorders (HR 2.06; 95% CI 1.07–3.95). In contrast, the association of cannabis use with suicide did not reach statistical significance even in crude analysis (HR 2.60; 95% CI 0.77–8.78).
Conclusion: Cannabis use in adolescence may increase risk of self-harm independent of adolescent psychopathology and other substance use
Trajectories of adolescent psychotic-like experiences and early cannabis exposure:results from a Finnish Birth Cohort Study
Abstract
Background: Longitudinal studies examining the effect of cannabis exposure (CE) on the prognosis of adolescents with psychotic-like experiences (PLEs) are scarce. We examined trajectories of mental health in adolescents with PLEs and cannabis exposure.
Methods: The Northern Finland Birth Cohort 1986 (n = 6552) with linkage to nationwide register data was used. Information on lifetime cannabis exposure was collected when participants were aged 15/16. Register-based outcome data on diagnoses made in clinical practice were obtained until age 33. Logistic regression was used to study the association of PLE/CE patterns and subsequent psychiatric disorders. The group with neither PLEs nor CE was utilized as the reference group. Parental psychiatric disorders, family structure, sex, frequent alcohol intoxications, daily smoking and illicit substance use other than cannabis were adjusted for.
Results: In all, 6552 subjects (49.2 % males) were included in analysis. PLEs with cannabis exposure were associated with any psychiatric disorder (OR = 2.59; 95 % CI 1.82–3.68), psychotic disorders (OR = 3.86; 95 % CI 1.83–8.11), mood disorders (OR 4.07; 95 % CI 2.74–6.04), depressive disorders (OR = 4.35; 95 % CI 2.93–6.48), anxiety disorders (OR = 2.06; 95 % CI 1.34–3.17) and substance use disorders (OR = 2.26; 95 % CI 1.13–4.50) compared to reference group. Effect sizes were greater for group with both PLEs and cannabis use than for group with PLEs only.
Conclusions: Early-onset cannabis use is an adverse prognostic marker for adolescents with PLEs after extensive confounder control including other substance use
Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis
Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p  0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice
Cognitive subtypes in recent onset psychosis: distinct neurobiological fingerprints?
In schizophrenia, neurocognitive subtypes can be distinguished based on cognitive performance and they are associated with neuroanatomical alterations. We investigated the existence of cognitive subtypes in shortly medicated recent onset psychosis patients, their underlying gray matter volume patterns and clinical characteristics. We used a K-means algorithm to cluster 108 psychosis patients from the multi-site EU PRONIA (Prognostic tools for early psychosis management) study based on cognitive performance and validated the solution independently (N = 53). Cognitive subgroups and healthy controls (HC; n = 195) were classified based on gray matter volume (GMV) using Support Vector Machine classification. A cognitively spared (N = 67) and impaired (N = 41) subgroup were revealed and partially independently validated (Nspared = 40, Nimpaired = 13). Impaired patients showed significantly increased negative symptomatology (pfdr = 0.003), reduced cognitive performance (pfdr < 0.001) and general functioning (pfdr < 0.035) in comparison to spared patients. Neurocognitive deficits of the impaired subgroup persist in both discovery and validation sample across several domains, including verbal memory and processing speed. A GMV pattern (balanced accuracy = 60.1%, p = 0.01) separating impaired patients from HC revealed increases and decreases across several fronto-temporal-parietal brain areas, including basal ganglia and cerebellum. Cognitive and functional disturbances alongside brain morphological changes in the impaired subgroup are consistent with a neurodevelopmental origin of psychosis. Our findings emphasize the relevance of tailored intervention early in the course of psychosis for patients suffering from the likely stronger neurodevelopmental character of the disease
Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis
Cannabis use during adolescence is associated with an increased risk of developing psychosis. According to a current hypothesis, this results from detrimental effects of early cannabis use on brain maturation during this vulnerable period. However, studies investigating the interaction between early cannabis use and brain structural alterations hitherto reported inconclusive findings. We investigated effects of age of cannabis initiation on psychosis using data from the multicentric Personalized Prognostic Tools for Early Psychosis Management (PRONIA) and the Cannabis Induced Psychosis (CIP) studies, yielding a total sample of 102 clinically-relevant cannabis users with recent onset psychosis. GM covariance underlies shared maturational processes. Therefore, we performed source-based morphometry analysis with spatial constraints on structural brain networks showing significant alterations in schizophrenia in a previous multisite study, thus testing associations of these networks with the age of cannabis initiation and with confounding factors. Earlier cannabis initiation was associated with more severe positive symptoms in our cohort. Greater gray matter volume (GMV) in the previously identified cerebellar schizophrenia-related network had a significant association with early cannabis use, independent of several possibly confounding factors. Moreover, GMV in the cerebellar network was associated with lower volume in another network previously associated with schizophrenia, comprising the insula, superior temporal, and inferior frontal gyrus. These findings are in line with previous investigations in healthy cannabis users, and suggest that early initiation of cannabis perturbs the developmental trajectory of certain structural brain networks in a manner imparting risk for psychosis later in life.</p